AI agents introduce new attack surfaces — prompt injection, agent hijacking, data exfiltration, hallucinated vulnerabilities, and unintended actions. As agents become more autonomous, security and reliability signals become decision-critical for any builder shipping agent-powered workflows.
This cluster covers AI security incidents, vulnerability disclosures, agent safety evaluations, and reliability signals from security researchers and frontier labs. Each signal links to the primary source for full context.
Use this page as a security watch list: catch emerging threats, review lab safety evaluations, and harden your agent pipelines before deploying to production.
Today, I’m talking with Helen Toner, the executive director of the Center for Security and Emerging Technology at Georgetown University. This episode is part two of our series on…
Jensen Huang has resigned from Nvidia following an affair, which could have ramifications for national security as the U.S. and China race to develop the most advanced AI infrastr…
We propose Synthesis Smuggling, a novel threat model in which an adversarial LLM infers sensitive information about a user from routine assistance-seeking interactions and stegano…
We study regret minimization in episodic Adversarial Markov Decision Processes (AMDPs) with unknown transitions and bandit feedback. In tabular AMDPs with $S$ states, $A$ actions,…
Release: llm 0.37.2 Fixes a security issue reported by Daniel de Araujo in GHSA-v9h7-jj4g-f862 and GHSA-r639-rr7r-x72w . LLM has a mechanism called extra-openai-models.yaml - now…
I sent out the October edition of my sponsors-only monthly newsletter . If you are a sponsor (or start a sponsorship now) you can access it here . This month: The October inflecti…